A5039468301- Meteorological Phenomena and Simulations
- Oceanographic and Atmospheric Processes
- Climate variability and models
- Methane Hydrates and Related Phenomena
- Manufacturing Process and Optimization
- Advanced Measurement and Metrology Techniques
- Reservoir Engineering and Simulation Methods
- Wireless Body Area Networks
- Atmospheric and Environmental Gas Dynamics
- Remote Sensing and LiDAR Applications
- Model Reduction and Neural Networks
- Remote Sensing in Agriculture
- Tree Root and Stability Studies
Massachusetts Institute of Technology
2020-2025
Australian National University
2023
Abstract We describe CATKE, a parameterization for fluxes associated with small‐scale or “microscale” ocean turbulent mixing on scales between 1 and 100 m. CATKE uses downgradient formulation that depends prognostic kinetic energy (TKE) variable diagnostic length scale includes dynamic convective adjustment (CA) component. With its length, predicts not just the depth spanned by plumes but also characteristic timescale, an important aspect of convection captured simpler static CA schemes. As...
We discuss the use of systematic ‘a posteriori’ calibration in development complicated (but theory-based) parameterizations. With calibration, model error is assessed using results forward simulations, thereby incorporating numerical error, stability, model-specific implementation details,  and alleviating need for explicit data all parameterized components. show how illuminates parameterization trade-off between reductions bias, producing better predictions, and...
We explore how neural differential equations (NDEs) may be trained on highly resolved fluid-dynamical models of unresolved scales providing an ideal framework for data-driven parameterizations in climate models. NDEs overcome some the limitations traditional networks (NNs) fluid dynamical applications that they can readily incorporate conservation laws and boundary conditions are stable when integrated over time. advocate a method employs 'residual' approach, which NN is used to improve upon...
We describe CATKE, a parameterization for ocean microturbulence with scales between 1 and 100 meters. CATKE is one-equation model that predicts diffusive turbulent vertical fluxes prognostic kinetic energy (TKE) diagnostic mixing length features dynamic convective adjustment (CA). With its length, not just the depth range where acts but also timescale over which occurs, an important aspect of convection captured by schemes. As result, can competition other processes such as baroclinic...
We describe CATKE, a parameterization for ocean microturbulence with scales between 1 and 100 meters. CATKE is one-equation model that predicts diffusive turbulent vertical fluxes prognostic kinetic energy (TKE) diagnostic mixing length features dynamic convective adjustment (CA). With its length, not just the depth range where acts but also timescale over which occurs, an important aspect of convection captured by schemes. As result, can competition other processes such as baroclinic...
<p>Parameterizations of turbulent mixing in the ocean surface boundary layer (OSBL) are key Earth System Model (ESM) components that modulate communication heat and carbon between atmosphere interior. OSBL turbulence parameterizations formulated terms unknown free parameters estimated from observational or synthetic data. In this work we describe development use a dataset called “LESbrary” generated by large number idealized, high-fidelity,...